Data Analytics Services

Contracting data analytics services becomes essential when your business needs to move beyond the basic reports provided by standard tools and delve into more intricate data analysis for strategic decision-making. This transition is typically marked by several indicators:

1. Need for In-Depth Insights: If you find yourself needing more detailed customer insights that go beyond what your CRM or ERP can provide, it’s time to consider advanced data analytics. This includes understanding customer behaviors, preferences, and segmenting customers for targeted marketing strategies.

2. Operational Efficiency: As your business scales, the need for operational efficiency and cost reduction becomes more crucial. Advanced data analytics can help create customized reports that combine various data points to optimize inventory, identify cost savings, and improve overall operational workflows.

3. Cross-Functional Analysis: When decision-making requires insights from across different departments, advanced data analytics tools can provide a unified view, uncovering critical business insights that can guide strategic initiatives and investments.

4. Predictive Analytics: If your business aims to be proactive rather than reactive, advanced data analytics can forecast trends, demand, and potential market opportunities, helping you strategize for future growth.

If your current tools are not meeting these needs, it may be time to explore adopting BI tools like PowerBI, Tableau, or Domo, which offer the sophistication required for these advanced analyses. The journey to implementing advanced data analytics should start with identifying your specific data needs, choosing the right BI tools, integrating your data sources, and building a data-driven culture within your organization.

If you are unsure of data analytics services are right for your business, do not hesitate to contact us for a free, detailed consultation.

Deciding between hiring an in-house analytics team and outsourcing to an agency depends on several factors that align with your company’s strategic direction, budget, and long-term objectives. Here are some considerations based on the information provided:

Advantages of Outsourcing to an Agency:

1. Diverse Expertise: Agencies typically offer a broader range of skills and expertise, which can be beneficial if your analytics needs are varied or if you require specialized knowledge.

2. Cross-Industry Experience: Partnering with an agency gives you access to best practices and insights gained from a wide array of industries, which can enrich your analytics approach.

3. Flexible Engagement Models: Agencies offer different collaboration models, from pay-as-you-go to dedicated resources, giving you flexibility in how you manage and budget for analytics services.

4. Scalability: With an agency, you can quickly scale your analytics capabilities up or down based on your current needs without the constraints of headcount and recruitment.

5. High Availability: Agencies prioritize client support and often plan their resources to ensure uninterrupted availability, which can be crucial for ongoing and time-sensitive analytics needs.

Disadvantages of Outsourcing:

1. Initial Onboarding: Consultants may require time to become familiar with your company and industry. However, this is often mitigated by the agency’s experience and ability to learn quickly.

2. Internal Resistance: Employees might be hesitant to work with external consultants. It’s essential to have management buy-in and foster a collaborative environment to ensure successful integration of external expertise.

3. Cost Considerations: While agencies might have a higher hourly cost compared to in-house salaries, they can provide value through flexibility, lack of long-term commitments, and by offering a variety of pricing models to suit different needs.

In conclusion, if you are looking for a broad range of analytics skills, need flexible and scalable support, and want to benefit from cross-industrial experience without the commitment of hiring full-time staff, outsourcing to an agency might be the right choice for you. However, if you prefer to have analytics expertise embedded within your team and are prepared to invest in hiring and training, building an in-house team could be beneficial. It’s recommended to weigh both options carefully and consider reaching out to agencies for quotes to better understand the potential costs and benefits.

Our services mainly cater to mid sized companies that have reached an inflection point where they can no longer effectively manage their operations, sales, marketing using Excel and Google Sheets. We cover the full spectrum of services such as data analytics consulting, data engineering, database administration, business intelligence and data science.

We can take care of the entire process of setting up an effective data analytics architecture from scratch or alternatively, however we can also help with targeted modular services.

For example, some of our customers have reached out to us when they needed to speed up the development and delivery of dashboards. As such, we helped them with Business Intelligence development while they chose to keep data engineering capabilities in house.

There are some other examples where large multinational companies have asked for our support and expertise to audit the work of other 3rd party contractors they were working with.

The take away is that we offer both end to end integrated services or modular, targeted assistance where needed.

We have worked with Affiliate Marketing, FMCG, Healthcare, Manufacturing, Transportation and Airlines, Logistics, SaaS and IT, Media and Advertising, Telecomm, Retail and Dealership companies.

Absolutely, please navigate to our Case Studies page and browse through the examples we have showcased there.

The greatest differentiator consists in our expertise in Lean Six Sigma, Business Analysis and Strategic Planning.

With more than 8 years of experience in multiple industries, we have been exposed to both tactic and strategic activities which is why we know that any data analytics solution we are developing has to firstly support and alleviate the most important pain points of your business.

We always prioritize projects to ensure that we have the highest impact with the least amount of effort and costs.

We understand that data privacy and security are paramount. Here’s how we safeguard your data:

• Ownership and Control: When we develop your data infrastructure, you have complete ownership and control over the architecture, systems, software, and—most critically—the data itself.
• In-Ecosystem Work: Our team operates within your infrastructure, avoiding any data transfer outside your secured ecosystem, ensuring data residency and sovereignty.
• Advanced Security Measures:
  • We implement and use SSH keys and VPNs for secure connections.
  • IP whitelisting and OAuth APIs are standard practice for controlled access.
  • Data encryption both in transit and at rest to protect your information.
  • Frequent password rotations to maintain security integrity.
• Compliance and Standards:
  • Our processes are designed to align with GDPR and CCPA.
  • We readily adapt to meet any specific requirements of your internal security policies.

Apart from implementing widely know best cybersecurity practices, currently we do not have specialized cyber security personnel which is why we recommend and welcome 3rd party or your inhouse resources to regularly test our infrastructures.

Additionally, we understand the importance of accountability and are willing to explore obtaining insurance coverage that addresses potential damages directly attributable to our services. While we are dedicated to the highest standards of excellence and vigilance, we also recognize the necessity of defining liability.

In the unlikely event of damages and unless specifically insured for, our liability is capped at the total amount billed for our services in the preceding six months of our collaboration. This provision is part of our commitment to transparency and mutual trust in our business relationships.

Your data’s security is our top priority, and we commit to maintaining the highest standards of cybersecurity practices.

For data analysis, we utilize a comprehensive suite of tools and technologies to handle every step of the data journey, ensuring robust, scalable, and insightful analytics.

ETL (Extract, Transform, Load):

• We use Python for scripting complex data processing tasks, alongside specialized ETL tools such as Alteryx, KNIME, and SPSS Modeler for workflow automation.
• For cloud-based ETL operations, we leverage AWS Glue, AWS Data Pipeline, Azure Data Factory, Azure Synapse, Google Cloud Dataflow, and Google Cloud Dataprep.
• BigQuery Data Transfer Service and DBT (Data Build Tool) are employed for seamless data integration and transformation within cloud data warehouses.

Datalakes:

• AWS Lake Formation and Azure Data Lake Storage solutions are in place for large-scale data storage and management.
• Google Cloud Storage is also used for its robustness and integration capabilities with Google Cloud services.

Data Warehouses:

• Our data warehousing needs are met with Amazon Redshift, Azure Synapse Analytics, Google BigQuery, and Snowflake, enabling high-performance analytics at scale.

Databases:

• We manage our structured data with Amazon Aurora, Amazon RDS, Azure SQL Database, Google Cloud SQL, PostgreSQL, and MariaDB.
• For NoSQL requirements, we rely on DynamoDB, Cosmos DB, BigQuery, MongoDB, Cassandra, and Elasticsearch for their flexibility and scalability.

Machine Learning:

• Our machine learning initiatives are powered by Scikit-learn, Amazon SageMaker, Amazon Forecast, Amazon Personalize, and Azure Machine Learning Studio for building and deploying models.
• We also utilize advanced platforms like Databricks, Azure Cognitive Services, TensorFlow, and Google Cloud AutoML for sophisticated AI and ML applications.

Business Intelligence:

• To turn data into actionable insights, we use Business Intelligence tools such as PowerBI, Tableau, Domo, QlikSense, MicroStrategy, Sisense, and Tibco Spotfire, which offer extensive visualization and reporting capabilities.

With this diverse toolkit, we’re equipped to tackle any data analysis challenge, ensuring our clients receive tailored, cutting-edge solutions for their specific needs.

Our approach of data visualization and reporting starts with a discussion with the end business users and stakeholders. We start by shadowing and understanding the process as it is and document the necessary views, functionalities and KPIs. We propose a solution, after which we work our way back to identify the necessary data, the underlying data sources and the way we are going to make the data available for reporting.

After preparing the data, we perform quality check to validate that our infrastructure is alligned with the underlying system we extracted the data from.

Next, we develop the dashboard by mixing best practices with user requirements to ensure that the final dashboard will be clear and user friendly.

When developing a dashboard, we like to take into account and implement your company’s branding guidelines. Data analytics is yet another opportunity to display and personalize and we want to take advantage of that real estate, especially when we are designing reports that are going to be available to the general public.

We pride ourselves with the fact that we always start with your strategic and annual objectives in mind to ensure that whatever we develop will directly support your most important goals.

By doing so, we ensure that your investments and our efforts are directed in the right place and that we prioritize the projects according to the impact they will generate.

Setting up data analytics infrastructures can take several months and building a data warehouse can take a long time, which is why we want to ensure that we are working on the right data.

We always say, there is no point in developing an employee turnover report when the company actually has a working capital issue driven by high inventory.

We know that data analytics adoption is a journey sometimes ridden with moving goalposts. We always encourage collaboration through a time and material or dedicated resources pricing model.

From our past experiences, we know that once our customers receive the first dashboards, ideas start pouring in and the more questions we answer, the more curiosities are born.

And this is our sign that we are doing our job efficiently and that data analytics has a real and immediate impact on your business.

We prioritize transparent communication, ensuring any challenges or adjustments in project scope are promptly discussed. Together, we reassess the initial objectives, evaluate any changes, and collaboratively decide on the best path forward, whether that involves adjusting timelines, expectations, or pricing.

Our goal is to be your long term, committed partner in analytics, ensuring continuous support and transparency throughout our collaboration.

If you’re considering our data analytics services, know that we prioritize a partnership approach to pricing. We want to ensure that our services align with your goals and provide clear value. Here’s an outline of how our pricing models can work for you:

1. Time and Material: Suited for projects where the scope may vary, this pay-as-you-go option offers the flexibility to adjust requirements as your project evolves. We’ll work with you to estimate the effort involved and ensure transparency and fairness in billing.

2. Retainer Fee: If you have ongoing analytics needs, our retainer service ensures dedicated support for a set number of hours each month. It’s a great way to secure our team’s availability without the commitment of a full-time hire.

3. Dedicated Resource: For businesses that anticipate a consistent, high-volume workload, we offer the option of dedicated resources. This model provides you with a team or individual fully focused on your data analytics needs for a sustained period, offering stability and deep integration with your operations.

We understand that each business’s needs are unique, and we’re committed to providing a pricing structure that reflects that.

For a detailed quote that’s tailored to your business’s specific data analytics requirements, please don’t hesitate to reach out to us. Our team is ready to discuss your objectives and how we can align our services for the best outcome.

The duration of a data analytics project varies greatly depending on its scope and complexity.

For specific tasks like data collection, web scraping, or single dashboard development, projects can range from a few days to two weeks.

More comprehensive projects, such as developing data warehouses and dashboards for multiple departments, from executive to operational levels, may span several months to even years.

We’re committed to flexibility and can scale our resources to meet project deadlines as needed. While we’ve shifted focus towards longer-term collaborations, our goal remains to provide tailored, impactful data analytics solutions that foster enduring partnerships.

Engaging with our data analytics services is a simple and straight forward process, ensuring we align with your business needs every step of the way.

Here’s how it works:

Before Contract Engagement

1. Initial Consultation: It all starts with booking a meeting where we discuss your business objectives and how our data analytics services can align with your goals. We conduct a detailed discussion to understand your business strategy and objectives. This helps us explain and show how data can be transformed into actionable insights for your organization.

2. Tailored Proposal: Based on our discovery meeting, we draft a custom proposal outlining the approach, services offered, and the estimated impact on your business.

3. Contract Finalization: After reviewing the proposal with you and incorporating any feedback, we finalize the terms and sign the contract, setting the stage for our collaboration.

After Contract Engagement

1. Onboarding & Data Integration: Our team sets up the necessary infrastructure for data ingestion, processing, and reporting, ensuring a smooth start to our partnership.

2. Custom Solution Implementation: We implement the bespoke data solution that includes setting up infrastructure, integrations, and any agreed-upon dashboards.

3. Training & Capacity Building: To ensure you get the most out of our services, we provide comprehensive training for your staff on the new systems and tools.

4. Ongoing Support & Optimization: We offer continuous support, including performance monitoring and optimization, to ensure the solutions evolve with your business.

For more detailed information and to get started with transforming your data into strategic assets, contact us for a personalized consultation.

Absolutely, we encourage you to read the Testimonials section on this page or from the homepage.

At Witanalytica, staying at the forefront of data analytics is central to our approach. We actively keep ourselves informed through various channels, including industry news, to ensure we’re aware of the latest developments.

Our team personally tests emerging technologies, often being among the first to access new tools and features through early sign-ups and beta programs. We also delve into product releases and updates, ensuring that we understand the capabilities and applications of new technologies. Beyond external research, we dedicate time for internal projects, experimentation, and training.

This hands-on approach allows us to not only stay updated but also to critically evaluate and integrate new technologies and methods into our solutions, ensuring our clients always benefit from cutting-edge analytics.

At Witanalytica, ensuring the accuracy and reliability of our data analysis is foundational to our approach. We adhere to stringent data quality standards, focusing on accuracy, completeness, consistency, and reliability.

Our process involves rigorous data validation techniques to minimize errors. We tackle common data quality challenges, such as incomplete data, duplicates, integration issues, and outdated information, by implementing best practices like setting mandatory fields, using data cleaning tools, standardizing data across systems, and establishing regular data refresh schedules.

To maintain the highest data quality, we also ensure data security, assign clear accountability and ownership of data sets, and conduct regular data audits. This comprehensive approach not only mitigates the risk of inaccurate insights but also supports informed decision-making and maintains our clients’ trust.

For a deeper dive into our data quality assurance practices and the importance of high-quality data in analytics, feel free to read more in our detailed article: Data Quality: How to Ensure Your Data Analytics Deliver Accurate Insights

After a project’s completion, our support at Witanalytica doesn’t just end. We actively monitor ETL processes, data sources, and dashboards for alerts and triggers to ensure continuous, smooth operation.

Maintenance of existing scripts and dashboards takes precedence, ensuring they perform optimally before we embark on developing new ones. We offer flexible support options tailored to your needs — from a fixed maintenance fee to time-and-material billing for any necessary adjustments or maintenance. This approach allows us to swiftly adapt to changes, such as updates in APIs or products, ensuring your ETLs remain current.

Moreover, we’re committed to the success and adoption of our solutions. We regularly measure and monitor their effectiveness because we believe in delivering not just solutions, but value that is actively utilized and drives results. Our goal is to ensure that the solutions we develop are not only technically sound but also widely adopted and impactful.